Flame instability detection and identification in industrial furnaces

Abstract

Systems and methods for multi-channel detection of an instability in a furnace comprising a plurality of detectors are disclosed. Each of a plurality of detectors provides a first measurement related to the plurality of burners when the furnace is operating in a stable condition. A stable signal component representation is determined based on the first measurement from each of the plurality of detectors. Each of a plurality of detectors provides a second measurement related to the plurality of burners when the furnace is operating in an unknown state. An unstable signal component representation is determined based on the stable signal component representation and a second measurement from each of the plurality of detectors. An instability is detected based on the unstable signal component representation and an instability threshold.

What is claimed is: 
     
         1 . A method for detecting an instability in a furnace having a plurality of burners, the method comprising:
 obtaining from each of a plurality of detectors a first measurement related to the plurality of burners when the furnace is operating in a stable condition;   determining, based at least in part on the first measurement from each of the plurality of detectors, a stable signal component representation for the furnace;   obtaining from each of the plurality of detectors a second measurement related to the plurality of burners when the furnace is operating in an unknown state;   determining, based at least in part on the second measurement from each of the plurality of detectors and the stable signal component representation, an unstable signal component representation for the furnace; and   detecting, using at least one processor, an instability in the furnace based at least in part on the unstable signal component representation and an instability threshold.   
     
     
         2 . The method of  claim 1 , wherein the plurality of detectors comprises a plurality of pressure sensors. 
     
     
         3 . The method of  claim 1 , wherein the plurality of detectors comprises a plurality of vibration sensors. 
     
     
         4 . The method of  claim 1 , wherein the plurality of detectors comprises a plurality of video sensors. 
     
     
         5 . The method of  claim 1 , wherein the stable signal component representation for the furnace comprises a stable covariance matrix. 
     
     
         6 . The method of  claim 1 , wherein the unstable signal component representation for the furnace comprises an instability component covariance. 
     
     
         7 . The method of  claim 6 , wherein the instability component covariance is calculated based on a stable covariance matrix and a current covariance matrix. 
     
     
         8 . The method of  claim 7 , wherein the current covariance matrix is calculated based on the stable covariance matrix and a vector of the second measurement from each of the plurality of burners. 
     
     
         9 . The method of  claim 1 , wherein the instability threshold is compared against a detection test statistic. 
     
     
         10 . The method of  claim 9 , wherein the detection test statistic comprises a Neyman-Pearson detector. 
     
     
         11 . The method of  claim 9 , further comprising computing the detection test statistic based on an inverse of a stable covariance matrix. 
     
     
         12 . The method of  claim 9 , further comprising computing the detection test statistic based on an inverse of a current covariance matrix. 
     
     
         13 . The method of  claim 12 , wherein the inverse of the current covariance matrix is computed via matrix inversion lemma. 
     
     
         14 . The method of  claim 1 , wherein the plurality of detectors comprise one or more detectors of a first detector type and one or more detectors of a second detector type. 
     
     
         15 . The method of  claim 14 , wherein obtaining the first measurement comprises:
 obtaining a first time series of measurements from each of one or more detectors of a first detector type, the first time series of measurements from each of the one or more detectors of a first detector having a first sampling rate; and   obtaining a second times series of measurements from each of one or more detectors of a second detector type, the second time series of measurements from each of the one or more detectors of a second detector type having a second sampling rate.   
     
     
         16 . The method of  claim 15 , wherein the first time series of measurements includes the first measurement for each of the one or more detectors of a first detector type, and wherein the second time series includes the first measurement for each of the one or more detectors of a second detector type. 
     
     
         17 . The method of  claim 16 , further comprising converting the first time series of measurements and the second time series of measurements into a combined time series of measurements having a common sampling rate,
 wherein determining the stable signal component representation for the furnace comprises determining the stable signal component representation for the furnace based at least in part on the combined time series of measurements.   
     
     
         18 . The method of  claim 17 , wherein the common sampling rate comprises the first sampling rate. 
     
     
         19 . The method of  claim 17 , wherein the common sampling rate comprises a sampling rate other than the first sampling rate and the second sampling rate. 
     
     
         20 . The method of  claim 15 , wherein the first time series of measurements includes the second measurement for each of the one or more detectors of a first detector type, and wherein the second time series includes the second measurement for each of the one or more detectors of a second detector type. 
     
     
         21 . The method of  claim 20 , further comprising converting the first time series of measurements and the second time series of measurements into a combined time series of measurements having a common sampling rate,
 wherein determining the unstable signal component representation for the furnace comprises determining the unstable signal component representation for the furnace based at least in part on the combined time series of measurements.   
     
     
         22 . The method of  claim 15 , wherein the first time series of measurements comprises at least one video frame. 
     
     
         23 . The method of  claim 22 , further comprising converting the at least one video frame into a single value. 
     
     
         24 . The method of  claim 23 , wherein the at least one video frame is converted into a single value based on an intensity of each pixel of the at least one video frame. 
     
     
         25 . The method of  claim 22 , wherein the second time series of measurements comprises at least one value measured by a pressure sensor. 
     
     
         26 . The method of  claim 1 , further comprising identifying an unstable subset of burners based at least in part on the unstable signal component representation. 
     
     
         27 . The method of  claim 26 , wherein the unstable signal component representation comprises an instability component covariance. 
     
     
         28 . The method of  claim 26 , further comprising using eigenvalue composition of the unstable signal component representation to obtain at least one dominant eigenvector. 
     
     
         29 . The method of  claim 28 , wherein the at least one dominant eigenvector includes three components defining a point on a unit ball. 
     
     
         30 . The method of  claim 29 , further comprising clustering the point with a plurality of other points obtained from a plurality of previous dominant eigenvectors. 
     
     
         31 . The method of  claim 30 , further comprising identifying the unstable subset of burners based on the clustering. 
     
     
         32 . The method of  claim 31 , wherein historical data is used to identifying the unstable subset of burners. 
     
     
         33 . The method of  claim 29 , further comprising recovering a Green's function vector from the at least one dominant eigenvector. 
     
     
         34 . The method of  claim 33 , wherein the at least one dominant eigenvector is normalized to obtain the Green's function vector. 
     
     
         35 . The method of  claim 26 , wherein the unstable subset of burners comprises a single burner. 
     
     
         36 . The method of  claim 26 , wherein the unstable subset of burners comprises a plurality of burners. 
     
     
         37 . The method of  claim 26 , wherein the unstable subset of burners comprises a group of burners containing at least one unstable burner. 
     
     
         38 . A system for detecting an instability in a furnace having a plurality of burners, the system comprising:
 a plurality of detectors; and   at least one processor coupled to the plurality of detectors and configured to:
 obtain from each of the plurality of detectors a first measurement related to the plurality of burners when the furnace is operating in a stable condition, 
 determine, based at least in part on the first measurement from each of the plurality of detectors, a stable signal component representation for the furnace, 
 obtain from each of the plurality of detectors a second measurement related to the plurality of burners when the furnace is operating in an unknown state, 
 determine, based at least in part on the second measurement from each of the plurality of detectors and the stable signal component representation, an unstable signal component representation for the furnace, and 
 detect an instability in the furnace based at least in part on the unstable signal component representation and an instability threshold. 
   
     
     
         39 . The system of  claim 38 , configured for use in accordance with any of the methods described in  claims 1  through  37 .